TY - JOUR
T1 - General resource for ionospheric transient investigations (GRITI)
T2 - An open-source code developed in support of the Dinsmore et al. (2021) results
AU - Dinsmore, Ross
AU - Mathews, J. D.
AU - Urbina, Julio
N1 - Funding Information:
We thank Anthea Coster for providing valuable knowledge on delta-vTEC processing. This material is based upon work supported by the US National Science Foundation under Grant No. AGS-1241407 to The Pennsylvania State University. The GPS TEC data products and access through the Madrigal distributed data system are provided to the community by the Massachusetts Institute of Technology under support from US NSF grant AGS-1242204. We thank CEDAR and all other involved organizations for the Open Madrigal service that provides GPS/GNSS TEC datasets as well as incoherent scatter radar (ISR) datasets ( http://cedar.openmadrigal.org/index.html ). We thank GFZ German Research Centre for Geosciences’ Helmholtz Centre Potsdam for the Kp index data ( http://www.gfz-potsdam.de/en/kp-index/ ). We thank NASA's Space Physics Data Facility in Goddard Space Flight Center for the OMNIWeb service that provides OMNI data ( https://omniweb.gsfc.nasa.gov/ow_min.html ). We thank the AMPERE team, the AMPERE Science Center, and all other involved organizations for providing the Iridium-derived data products ( http://ampere.jhuapl.edu/index.html ). We thank Natural Resources Canada for access to the data from Canada's magnetic observatories ( https://www.geomag.nrcan.gc.ca/data-donnee/sd-en.php ). Data for the Madrigal's TEC processing is provided from the following organizations: UNAVCO, Scripps Orbit and Permanent Array Center, Institut Geographique National, France, International GNSS Service, The Crustal Dynamics Data Information System (CDDIS), National Geodetic Survey, Instituto Brasileiro de Geografia e Estatística, RAMSAC CORS of Instituto Geográfico Nacional de la República Argentina, Arecibo Observatory, Low-Latitude Ionospheric Sensor Network (LISN), Topcon Positioning Systems, Inc., Canadian High Arctic Ionospheric Network, Institute of Geology and Geophysics, Chinese Academy of Sciences, China Meteorology Administration, Centro di Ricerche Sismologiche, Système d'Observation du Niveau des Eaux Littorales (SONEL), RENAG: REseau NAtional GPS permanent, GeoNet - the official source of geological hazard information for New Zealand, GNSS Reference Networks, Finnish Meteorological Institute, SWEPOS - Sweden, Hartebeesthoek Radio Astronomy Observatory, Crustal Dynamics Data Information System (CDDIS), Astronomical Institute of the University of Bern, TrigNet Web Application, South Africa, Australian Space Weather Services, RETE INTEGRATA NAZIONALE GPS, Estonian Land Board, and Virginia Tech Center for Space Science and Engineering Research. We also thank the contributors to Python 3 ( https://docs.python.org/3 ), NumPy [15] , Matplotlib [7] , Scipy [12] , h5py ( https://docs.h5py.org ), Numba [9] , Cartopy ( https://scitools.org.uk/cartopy ), Basemap ( https://matplotlib.org/basemap ), Astropy [13] , timezonefinder ( https://timezonefinder.readthedocs.io ), pytz ( https://github.com/stub42/pytz ), html2text ( https://github.com/Alir3z4/html2text ), and Spyder ( https://www.spyder-ide.org/ ).
Funding Information:
We thank Anthea Coster for providing valuable knowledge on delta-vTEC processing. This material is based upon work supported by the US National Science Foundation under Grant No. AGS-1241407 to The Pennsylvania State University. The GPS TEC data products and access through the Madrigal distributed data system are provided to the community by the Massachusetts Institute of Technology under support from US NSF grant AGS-1242204. We thank CEDAR and all other involved organizations for the Open Madrigal service that provides GPS/GNSS TEC datasets as well as incoherent scatter radar (ISR) datasets (http://cedar.openmadrigal.org/index.html). We thank GFZ German Research Centre for Geosciences? Helmholtz Centre Potsdam for the Kp index data (http://www.gfz-potsdam.de/en/kp-index/). We thank NASA's Space Physics Data Facility in Goddard Space Flight Center for the OMNIWeb service that provides OMNI data (https://omniweb.gsfc.nasa.gov/ow_min.html). We thank the AMPERE team, the AMPERE Science Center, and all other involved organizations for providing the Iridium-derived data products (http://ampere.jhuapl.edu/index.html). We thank Natural Resources Canada for access to the data from Canada's magnetic observatories (https://www.geomag.nrcan.gc.ca/data-donnee/sd-en.php). Data for the Madrigal's TEC processing is provided from the following organizations: UNAVCO, Scripps Orbit and Permanent Array Center, Institut Geographique National, France, International GNSS Service, The Crustal Dynamics Data Information System (CDDIS), National Geodetic Survey, Instituto Brasileiro de Geografia e Estat?stica, RAMSAC CORS of Instituto Geogr?fico Nacional de la Rep?blica Argentina, Arecibo Observatory, Low-Latitude Ionospheric Sensor Network (LISN), Topcon Positioning Systems, Inc. Canadian High Arctic Ionospheric Network, Institute of Geology and Geophysics, Chinese Academy of Sciences, China Meteorology Administration, Centro di Ricerche Sismologiche, Syst?me d'Observation du Niveau des Eaux Littorales (SONEL), RENAG: REseau NAtional GPS permanent, GeoNet - the official source of geological hazard information for New Zealand, GNSS Reference Networks, Finnish Meteorological Institute, SWEPOS - Sweden, Hartebeesthoek Radio Astronomy Observatory, Crustal Dynamics Data Information System (CDDIS), Astronomical Institute of the University of Bern, TrigNet Web Application, South Africa, Australian Space Weather Services, RETE INTEGRATA NAZIONALE GPS, Estonian Land Board, and Virginia Tech Center for Space Science and Engineering Research. We also thank the contributors to Python 3 (https://docs.python.org/3), NumPy [15], Matplotlib [7], Scipy [12], h5py (https://docs.h5py.org), Numba [9], Cartopy (https://scitools.org.uk/cartopy), Basemap (https://matplotlib.org/basemap), Astropy [13], timezonefinder (https://timezonefinder.readthedocs.io), pytz (https://github.com/stub42/pytz), html2text (https://github.com/Alir3z4/html2text), and Spyder (https://www.spyder-ide.org/).
Publisher Copyright:
© 2021 The Authors
PY - 2021/1
Y1 - 2021/1
N2 - The analysis techniques and the corresponding software suite GRITI (General Resource for Ionospheric Transient Investigations) are described. GRITI was used to develop the Dinsmore et al. [2] results, which found a novel classification of traveling ionospheric disturbances (TIDs) called semi-coherent ionospheric pulsing structures (SCIPS). The any-geographic range (local-to-global), any-azimuth angle keogram algorithm used to analyze SCIPS in that work is detailed. The keogram algorithm in GRITI is applied to detrended vTEC (vertical Total Electron Content) data, called delta-vTEC herein, in Dinsmore et al. [2] and the follow-on paper Dinsmore et al. [3], but is also applicable to any other two-dimensional dataset that evolves through time. GRITI's delta-vTEC processing algorithm is also described in detail, which is used to provide the delta-vTEC data for Dinsmore et al. [3]. • We detail a keogram algorithm for analysis of delta-vTEC data in Dinsmore et al. [2] and the follow-on paper Dinsmore et al. [3]. • We detail a delta-vTEC processing algorithm that converts vTEC data to delta-vTEC through detrending that is used to provide the delta-vTEC data used in Dinsmore et al. [3]. • GRITI is an open-source Python 3 analysis codebase that encompasses the delta-vTEC processing and keogram algorithms. GRITI has additional support for other data sources and is designed for flexibility in adding new data sources and analysis methods. GRITI is available for download at: https://github.com/dinsmoro/GRITI.
AB - The analysis techniques and the corresponding software suite GRITI (General Resource for Ionospheric Transient Investigations) are described. GRITI was used to develop the Dinsmore et al. [2] results, which found a novel classification of traveling ionospheric disturbances (TIDs) called semi-coherent ionospheric pulsing structures (SCIPS). The any-geographic range (local-to-global), any-azimuth angle keogram algorithm used to analyze SCIPS in that work is detailed. The keogram algorithm in GRITI is applied to detrended vTEC (vertical Total Electron Content) data, called delta-vTEC herein, in Dinsmore et al. [2] and the follow-on paper Dinsmore et al. [3], but is also applicable to any other two-dimensional dataset that evolves through time. GRITI's delta-vTEC processing algorithm is also described in detail, which is used to provide the delta-vTEC data for Dinsmore et al. [3]. • We detail a keogram algorithm for analysis of delta-vTEC data in Dinsmore et al. [2] and the follow-on paper Dinsmore et al. [3]. • We detail a delta-vTEC processing algorithm that converts vTEC data to delta-vTEC through detrending that is used to provide the delta-vTEC data used in Dinsmore et al. [3]. • GRITI is an open-source Python 3 analysis codebase that encompasses the delta-vTEC processing and keogram algorithms. GRITI has additional support for other data sources and is designed for flexibility in adding new data sources and analysis methods. GRITI is available for download at: https://github.com/dinsmoro/GRITI.
UR - http://www.scopus.com/inward/record.url?scp=85111062928&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85111062928&partnerID=8YFLogxK
U2 - 10.1016/j.mex.2021.101456
DO - 10.1016/j.mex.2021.101456
M3 - Article
C2 - 34430337
AN - SCOPUS:85111062928
SN - 2215-0161
VL - 8
JO - MethodsX
JF - MethodsX
M1 - 101456
ER -